The impact of the use of employee functional flexibility on patient safety
Bibliographic record
Abstract
Purpose The purpose of this study is to examine the effect of the use of unit-level functional flexibility on one particular patient outcome, unit-acquired pressure ulcers, and the potential moderating influences of coworker support and workload. Design/methodology/approach This study uses an archival approach, examining data from 68 hospital units. Findings The results indicate that a unit's higher use of functionally flexible nurses in one-quarter was associated with a higher number of pressure ulcers among the unit's patients the following quarter. This detrimental effect was significantly diminished when coworker support within the unit was high. Unit-level nurse workload did not have any moderating influence. Research limitations/implications One of the scholarly contributions of this study is that it links greater use of functionally flexible employees to a negative patient safety outcome at the unit level. As most of the variables used in the study were archival measures, future research could examine the replicability of these findings using other indicators and measures. Practical implications Beyond healthcare settings, the results prompt managers in industries where there has been growing use of functional flexibility (e.g., banking) to think about the associated unintended negative consequences. That said, the results also point to coworker instrumental support as a means by which to mitigate negative outcomes. Originality/value Although functional flexibility has been shown to positively correlate with a number of organizational performance indicators, this is one of the very few studies that has examined its negative consequences, particularly on patient safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".